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You will design and execute assessments to measure AI model capabilities and safety while developing rubrics for grading model outputs. Additionally, you will analyze error patterns, compare model performance, and document findings to improve evaluation benchmarks.
Join a specialist talent pool supporting human-data projects that evaluate AI models. You will help design and run assessments that measure model capabilities and contribute to AI safety and capability research.
Write questions and tasks that isolate and test specific model capabilities.
Develop rubrics that define strong, partial, and poor answers.
Create reference answers and edge cases to challenge AI models.
Grade model outputs against rubrics and explain scoring decisions.
Analyze failed answers, group error patterns, and document findings.
Compare multiple models using identical prompts.
Validate benchmarks and flag compromised or ineffective questions.
Participate in small user studies evaluating ratings or interactions with model outputs.
Zero to five years of professional experience.
Experience in QA or test engineering, assessment design, psychometrics, UX research, data analysis, ML evaluation, research support, or relevant subject-matter work involving question writing.
Experience writing test cases, exam questions, rubrics, or evaluation tasks, and reviewing work consistently against written criteria.
Comfort using spreadsheets or Python to organize and analyze results, and identifying and documenting error patterns.
Experience with evaluation tools such as Inspect, lm-eval-harness, HELM, or promptfoo is useful.
Clear written communication and the ability to compare AI model outputs or participate in user and rating studies.
Compensation is $30 to $60 per hour, depending on project, field, and experience. Payment is for hours worked.
Fully remote. Projects typically last from one week to several months.
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